The present invention relates to the field of robotics and automated guided vehicles. More particularly, the present invention relates to a navigational control system for autonomous vehicles.
The ultimate goal of a robotic system is to perform some useful function in place of a human counterpart. Benefits typically associated with the installation of fixed-location industrial robots are improved operational effectiveness, higher quality, reductions in manpower, greater efficiency, reliability, and cost savings. Additionally, robots perform tasks for which humans are incapable or ill-suited, and can operate in environments which are dangerous to humans.
The concept of mobility has always suggested an additional range of applications beyond that of the typical factory floor, wherein free-roaming robots may move about with an added versatility beyond that of stationary robotic systems and which offer the potential of even greater returns. In practice, however, the realization of this dream has not been fully realized.
A significant technological requirement of a truly mobile robot is the need to successfully interact with the physical objects and entities in its environment. A mobile robot must be able to navigate from a known position to a desired new location and orientation, and avoid any contact with fixed or moving objects while enroute.
As shown in FIG. 1, one category of autonomous mobile robot control may be referred to as "reflexive" or "guidepath" control. The term reflexive control refers to a navigational control loop which reacts (in a reflexive manner) to the sensed position of some external guiding reference, as will be discussed later. The purpose of reflexive control is to free a human operator from the requirement of having to steer the moving platform. This type of control scheme is commonly employed on automated guided vehicles (AGV's).
Automated guided vehicles have found extensive use in automated factories and warehouses for material transfer, in modern office scenarios for material and mail pickup and delivery, and in hospitals for delivery of meals and supplies to nursing stations, to name but a few. Such devices are guided while in transit by a number of schemes, the most common being some type of stripe or wire guidepath that is detected by sensors installed on the front of the platform and used to servo-control the steering mechanism so as to cause the vehicle to follow the intended route. Reflexive guidance schemes of this type may be divided into two general categories: 1) those which sense and follow the audio frequency (AF) or radio frequency (RF) field from a closed-loop wire embedded in the floor, and, 2) those which optically sense and follow some type of stripe affixed to the floor surface.
Various implementations of the stripe-following concept exist, including the most simplistic case of tracking a high-contrast (dark-on-light, light-on-dark) line. Other methods include systems which track a special reflective tape illuminated by an onboard light source, and a system developed by Litton Corporation which tracks a chemical stripe that glows when irradiated by ultraviolet energy.
Advantages of reflexive control are seen primarily in the improved efficiency and reduction of manpower which arises from the fact that an operator is no longer required to guide the vehicle. Large numbers of AGV's can operate simultaneously in a plant or warehouse, scheduled and controlled by a central computer which monitors overall system operation and vehicle flow with minimal or no human intervention. Navigational problems do not arise because the vehicles are following designated routes suitably encoded so as to provide a positional reference at all times for any given vehicle. The central computer can thus keep track of the exact location of all vehicles in the system. Communication with individual vehicles is accomplished over RF links or directional near-infrared modulated light beams, or other means. The fundamental disadvantage of reflexive control is the lack of flexibility in the system whereby a vehicle cannot be commanded to go to a new location unless the guide path is first modified. This is a significant factor in the event of changes to product flow lines in assembly plants, or in the case of a security robot which must investigate a potential break-in at a designated remote location.
Again referring to FIG. 1, a second type of autonomous control system may be referred to as "unrestricted" or "absolute world coordinate" control, which implies the ability of a free-roaming platform to travel anywhere so desired, subject to nominal considerations of terrain traversability. Many potential applications await an indoor mobile robot that could move in a purposeful fashion from room to room without following a set guidepath, with the intelligence to avoid objects, and if necessary, choose alternative routes of its own planning.
Apart from the field of AGV's, however, successful implementation of robotics technology to date has been almost exclusively limited to fixed-place industrial robots operating in high-volume manufacturing scenarios that justify the intense "teach pendant" programming required to train the robot, which then repeats the taught sequences over and over under tightly controlled, highly structured conditions. The increasing use of process control and feedback sensors has started a trend toward implementation of adaptive control in flexible automation. Attempts to transfer this specialized assembly-line technology over into the unstructured world of a mobile robot, however, have met with little success; the problems are fundamentally different.
The difficulties can be directly related to the unstructured nature of the mobile robot's operating environment. Industrial process control systems used in flexible manufacturing (factory of the future) scenarios rely on carefully placed sensors which exploit the target characteristics. Background conditions are arranged to provide minimal interference, and often aid in the detection process by increasing the on-off differential or contrast. In addressing the collision avoidance requirements of a mobile robot, however, the nature and orientation of the target surface, such as an obstruction, is not known with any certainty. Yet, to be effective, the system must be able to detect a wide variety of surfaces with varying angles of incidence. Control of background and ambient conditions may not be possible. Preprogrammed information regarding the relative positions, orientations, and nature of objects within the field-of-view of the sensors becomes difficult indeed for a moving platform.
Specialized sensors specifically intended to cope with these problems must be coupled with some type of "world modeling" capability that represents the relative/absolute locations of objects detected by these sensors in order to provide a mobile platform with sufficient awareness of its surroundings to allow it to move about in a realistic fashion. The accuracy of this model, which must be constructed and refined in a continuous fashion as the robot moves about its workspace, is directly dependent throughout this process upon the validity of the robot's perceived location and orientation. Accumulated dead-reckoning errors soon render the information entered into the model invalid in that the associated geographical reference point for data acquired relative to the robot's position is incorrect. As the accuracy of the model degrades, the ability of the robot to successfully navigate and avoid collisions diminishes rapidly, until it fails altogether. A robust navigational scheme that preserves the validity of the world model for free-roaming platforms has remained an elusive research goal, and for this reason many potential applications of autonomous mobile robots are not yet practical.
Therefore, there is a need for a robust vehicle guidance system which is capable of guiding a vehicle such as a mobile platform to a dynamically determined destination along a path which automatically avoids randomly distributed obstacles that may be positioned between the vehicle and the destination.